DBMS > Kdb vs. SQLite vs. Tarantool vs. TerarkDB vs. Vertica

System Properties Comparison Kdb vs. SQLite vs. Tarantool vs. TerarkDB vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Widely used embeddable, in-process RDBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Time Series DBMS
Vector DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Key-value store

Relational DBMS

Column oriented

Secondary database models

Relational DBMS

Spatial DBMS

with Tarantool/GIS extension

Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

kx.com

www.sqlite.org

www.tarantool.io

github.com/bytedance/terarkdb

www.vertica.com

Technical documentation

code.kx.com

www.sqlite.org/docs.html

www.tarantool.io/en/doc

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

vertica.com/documentation

Developer

Kx Systems, a division of First Derivatives plc

Dwayne Richard Hipp

ByteDance, originally Terark

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2000

kdb was released 2000, kdb+ in 2003

2000

2008

2016

2005

Current release

3.6, May 2018

3.46.0 (23 May 2024), May 2024

2.10.0, May 2022

12.0.3, January 2023

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

Public Domain

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

commercial

restricted open source version available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C++

Server operating systems

Linux
OS X
Solaris
Windows

server-less

BSD
Linux
macOS

Linux

Data scheme

yes

dynamic column types

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

string, double, decimal, uuid, integer, blob, boolean, datetime

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

table attribute 'grouped'

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like query language (q)

yes

SQL-92 is not fully supported

Full-featured ANSI SQL support

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Open binary protocol

C++ API
Java API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

C++
Java

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

Lua, C and SQL stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

with views

yes

yes, before/after data modification events, on replication events, client session events

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, full featured in-memory storage engine with persistence

yes

User concepts

Access control

rights management via user accounts

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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Cost-based models and subscription-based models are both available. One license is...
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